2 papers
cs.LG2026
Reasoning emerges from constrained inference manifolds in large language models
Yanbiao Ma, Fei Luo, Linfeng Zhang +10
Reasoning in large language models is predominantly evaluated through labeled benchmarks, conflating task performance with the quality of internal inference. Here we study reasonin…
cs.CL2024
ICLEval: Evaluating In-Context Learning Ability of Large Language Models
Wentong Chen, Yankai Lin, ZhenHao Zhou +4
In-Context Learning (ICL) is a critical capability of Large Language Models (LLMs) as it empowers them to comprehend and reason across interconnected inputs. Evaluating the ICL abi…